Integrated Gasification Combined Cycle (IGCC) technology continues progressing as an attractive technology for clean and efficient electric power generation, such as may be generated from abundant carbonaceous materials, e.g., coal and other relatively low-cost fuels. At the front end of IGCC is a process known as gasification, which is a partial oxidation process that transforms the fuel (e.g., coal) into a stream of combustible synthesis gas (syngas). IGCC is environmental-friendly because pollution-causing emissions (e.g., SOx, NOx, mercury, particulates, etc.) may be substantially removed from the syngas stream before combustion occurs. While IGCC technology intrinsically holds significant potential for clean and efficient power generation, there are opportunities yet to be exploited to improve IGCC power generation for enhanced reliability, availability, efficiency and flexibility.
It is known that present techniques for operation of an IGCC power plant tend to be based on simplistic control procedures, as may be conveyed to an operator by way of rigid and cumbersome operator guidelines, not necessarily designed to achieve any meaningful optimization strategy, such as may be due to limited online information for monitoring and controlling the IGCC plant. For example, instead of relying on fundamental metrics, which may directly indicate actual physical performance of the plant, such as carbon conversion efficiency, etc., subordinate metrics, which may just tangentially indicate performance of the plant, such as oxygen-to-carbon ratio, are often substituted in an attempt to assess plant performance. Moreover, present plant operation relies on operators having to “tweak” single control knobs or dials (e.g., oxygen-to-carbon ratio) to achieve some basic operation, which may be subject to variability, as may be introduced due to the level of experience of a given operator. The foregoing approach generally results in a conservative (i.e., suboptimal control), which does not fully achieve the potential efficiency of the IGCC plant.
In view of the foregoing considerations, it would be desirable to formulate a model predictive control (MPC) strategy, where the IGCC plant may be cost-effectively operated with a higher degree of flexibility. For example, it would be desirable to formulate a multivariable predictive control strategy, which may be dynamically tailored essentially in real-time to a respective operational mode of the IGCC plant, or may be dynamically tailored to a respective transient condition of the IGCC plant, such as when the plant transitions from one operational mode to another operational mode. It would be further desirable to formulate a control strategy, which may be dynamically adaptable to various scenarios of plant operation, such as operation with different fuels or fuel blends, or under varying power generating conditions, while maintaining or improving efficiency and availability of the IGCC plant.